+ iRt^RIHt^RIHtHtHtHtHtH t H t ]'d^RI t ] !R4t !RR]]] ,4tRtRR ltR R ltR R ltRRltRRltRRltR#)aOptional DataFrame conversion for pykalshi objects. Requires pandas: pip install pykalshi[dataframe] Usage: # Methods return DataFrameList - call .to_dataframe() directly: df = client.portfolio.get_positions().to_dataframe() df = client.portfolio.get_fills().to_dataframe() df = client.get_markets().to_dataframe() # Or use the standalone function: from pykalshi import to_dataframe df = to_dataframe(positions) ) annotations) TYPE_CHECKINGAnyGenericSequence SupportsIndexTypeVaroverloadNTcva]tRt^tRt]RRl4t]RRl4tV3RltRRltR V3R lltR t V;t #) DataFrameLista A list subclass with DataFrame conversion support. Behaves exactly like a normal list, but adds a .to_dataframe() method for convenient conversion to pandas DataFrames. Example: positions = client.portfolio.get_positions() # Returns DataFrameList df = positions.to_dataframe() c V^8dQhRRRR/#)indexrreturnr )formats"Y/home/wkmabra/.openclaw/workspace/venv/lib/python3.14/site-packages/pykalshi/dataframe.py __annotate__DataFrameList.__annotate__&s99919c R#Nrselfrs&&r __getitem__DataFrameList.__getitem__%s69rc V^8dQhRRRR/#)rrslicerzDataFrameList[T]r)rs"rrr(s@@@+;@rc R#rrrs&&rrr's=@rc h<\SV`V4p\V\4'd \ V4#V#r)superr isinstancerr )rrresult __class__s&& rrr*s/$U+ eU # # ( ( rcV^8dQhRR/#)rr pd.DataFramer)rs"rrr0s""l"rc \V4#)z[Convert this list to a pandas DataFrame. Requires pandas: pip install pykalshi[dataframe] ) to_dataframe)rs&rr(DataFrameList.to_dataframe0s D!!rcV^8dQhRR/#)rrstrr)rs"rrr7s66#6rc (<R\SV`4 R2#)zDataFrameList())r!__repr__)rr$s&rr.DataFrameList.__repr__7s 0 23155rr) __name__ __module__ __qualname____firstlineno____doc__r rr(r.__static_attributes__ __classcell__)r$s@rr r s:99 @@ "66rr cF^RIpV# \d\R4Rhi;i)z.Lazy import pandas with helpful error message.Nz]pandas is required for DataFrame conversion. Install it with: pip install pykalshi[dataframe])pandas ImportError)pds r_import_pandasr;;s5  ?  s c V^8dQhRRRR/#robjrrr&r)rs"rrrGs-"-"c-"l-"rch\4p^RIHpHp\ W4'd \ W4#\ W4'd \ W4#\ V\4'dI\ V\\34'g-\V4^8XdVP!4#\W4#\W4#)aConvert a pykalshi object or list of objects to a pandas DataFrame. Supports: - Lists of Pydantic models (PositionModel, FillModel, etc.) - Lists of domain objects (Market, Order, Event, Series) - CandlestickResponse (extracts candlesticks with flattened price data) - Single Pydantic models (returns single-row DataFrame) Args: obj: A pykalshi object or list of objects. Returns: A pandas DataFrame with appropriate columns. Examples: >>> positions = client.portfolio.get_positions() >>> df = to_dataframe(positions) >>> markets = client.get_markets(limit=100) >>> df = to_dataframe(markets) >>> candles = market.get_candlesticks(start_ts, end_ts) >>> df = to_dataframe(candles) )CandlestickResponseOrderbookResponse)r;modelsr@rAr"_candlesticks_to_df_orderbook_to_dfrr+byteslen DataFrame_sequence_to_df _single_to_df)r>r:r@rAs& rr(r(Gs2  B?#++"3++#))((#x  C#u)F)F s8q=<<> !s''  !!rc V^8dQhRRRR/#r=r)rs"rrrws  s < rc>\V4pVP!V.4#)z2Convert a single object to a single-row DataFrame. _extract_datarG)r>r:datas&& rrIrIws  D << rc V^8dQhRRRR/#)ritemsrrr&r)rs"rrr}s!!8!L!rcdVUu.uFp\V4NK ppVP!V4#uupi)z-Convert a sequence of objects to a DataFrame.rL)rPr:itemrecordss&& rrHrH}s//45ut}T"uG5 <<  6s-c V^8dQhRRRR/#)rr>rrdictr)rs"rrrsIIsItIrc\VR4'd9\VPR4'dVPPRR7#\VR4'dVPRR7#\V\4'dV#\VR4'dHVP P 4UUu/uF wrVPR4'dKWbK" upp#\R\V4P R24huuppi) zExtract a flat dict from an object. Handles: - Domain objects with .data attribute (Market, Order, Event, Series) - Pydantic models with .model_dump() - Plain dicts Uses mode='json' to serialize enums as their string values. rN model_dumpjson)mode__dict___zCannot convert z to DataFrame) hasattrrNrWr"rUrZrP startswith TypeErrortyper0)r>kvs& rrMrMssF, ? ?xx"""//sL!!~~6~**#t sJ!$!3!3!5O!5Q\\#=N!5OO od3i&8&8%9G HHPs 6DDc V^8dQhRRRR/#rresponserrr&r)rs"rrrs#lrc .pVPFpRVPRVPRVPRVP/pVP 'd+R F$p\ VP VR4pVfK WdV&K& VPV4K VP!V4pRVP9d/\V4^8dVP!VR,RR7VR&V#) zFConvert CandlestickResponse to DataFrame with flattened price columns.ticker end_period_tsvolume open_interestNs)unit timestamp)openhighlowclosemean) candlesticksrfrgrhripricegetattrappendrGcolumnsrF to_datetime)rdr:rScandlerecordfieldvaluedfs&& rrCrCsG'' hoo V11 fmm V11   <<<A eT:$$)5MB v(" g B"**$R1..O)<3G; Irc V^8dQhRRRR/#rcr)rs"rrrss<rc .pVPP'd7VPPFwr4VPRRRVRV/4K VPP'd7VPPFwr4VPRRRVRV/4K VP!V4p\ V4^8d(VP RR.RR.R7PRR 7pV#) zConvert OrderbookResponse to DataFrame with price levels. Returns DataFrame with columns: side, price, quantity Sorted by price descending within each side. sideyesrsquantitynoF) ascendingT)drop) orderbookrrurrGrF sort_values reset_index)rdr:rSrsrr|s&& rrDrDs G'1155OE NNFE7E:xP Q 6'1144OE NNFD'5*hO P 5 g B 2w{ ^^ W en  +4+  Ir)r4 __future__rtypingrrrrrrr r8r:r listr r;r(rIrHrMrCrDrrrrs_ #ZZZ CL6D'!*6B -"` ! I::r